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Ai grid (#1344)
* feat: add AI grid trading and market regime classification - Add GridTrader interface with PlaceLimitOrder, CancelOrder, GetOrderBook - Implement GridTrader for all exchanges (Binance, Bybit, OKX, Bitget, Hyperliquid, Aster, Lighter) - Add grid engine with ATR-based boundary calculation and fund distribution - Add market regime classification documents (Chinese/English) - Add GridConfigEditor component for frontend configuration * fix: implement GetOpenOrders for Lighter exchange * debug: add logging for Lighter GetActiveOrders API call * fix: correct Lighter API response parsing for GetOpenOrders - Changed response field from 'data' to 'orders' to match Lighter API - Updated OrderResponse struct to match Lighter's actual field names - Fixed field types: price/quantity as strings, is_ask for side * feat: implement GetOpenOrders for Aster, OKX, Bitget exchanges - Aster: uses /fapi/v3/openOrders endpoint - OKX: uses /api/v5/trade/orders-pending and orders-algo-pending - Bitget: uses /api/v2/mix/order/orders-pending and orders-plan-pending * fix: address code review issues for GetOpenOrders - Add error logging for OKX/Bitget API failures (was silently swallowed) - Fix Lighter position side logic to handle reduce-only orders - Change verbose debug logs from Infof to Debugf level * fix: provide FromAccountIndex and ApiKeyIndex for Lighter nonce auto-fetch Root cause: SDK requires these fields to fetch nonce from API, otherwise nonce gets cached/stuck * fix: use auth query parameter instead of Authorization header for Lighter API * test: add Lighter API authentication tests and diagnostic tools * fix(grid): add leverage setting before order placement CRITICAL BUG FIX: - Call SetLeverage() in GridTraderAdapter.PlaceLimitOrder() - Set leverage during grid initialization - Log leverage setting results * fix(grid): prevent CancelOrder from canceling all orders CRITICAL BUG FIX: - CancelOrder no longer calls CancelAllOrders - Try exchange-specific CancelOrder if available - Return error if individual cancellation not supported * fix(grid): add total position value limit check CRITICAL: Prevent excessive position accumulation - New checkTotalPositionLimit() function - Checks current + pending + new order value - Rejects orders that would exceed TotalInvestment x Leverage - Logs clear error messages when limit exceeded * feat(grid): implement stop loss execution CRITICAL: Add code-level stop loss protection - New checkAndExecuteStopLoss() function - Checks each filled level against StopLossPct - Automatically closes positions exceeding stop loss - Called during every grid state sync * feat(grid): add breakout detection and auto-pause CRITICAL: Detect price breakout from grid range - New checkBreakout() function to detect upper/lower breakouts - Auto-pause grid on significant breakout (>2%) - Cancel all orders when breakout detected - Prevent continued losses in trending market - Minor breakouts (1-2%) logged for AI consideration * feat(grid): enforce max drawdown limit with emergency exit CRITICAL: Add drawdown protection - New checkMaxDrawdown() function tracks peak equity - emergencyExit() closes all positions and cancels orders - Auto-pause grid when MaxDrawdownPct exceeded - Protect capital from excessive losses * feat(grid): enforce daily loss limit - Add checkDailyLossLimit() function to check if daily loss exceeds limit - Track daily PnL with auto-reset at midnight - Pause grid when DailyLossLimitPct exceeded - Add updateDailyPnL() helper for realized PnL tracking - Prevent excessive single-day losses * fix(grid): update daily PnL when stop loss is executed The updateDailyPnL() function was added but never called, leaving DailyPnL always at 0 and preventing daily loss limit checks from triggering. This fix updates DailyPnL and TotalProfit directly in checkAndExecuteStopLoss() when a stop loss is executed. We update directly rather than calling updateDailyPnL() because the mutex is already held in that function. * feat(grid): add automatic grid adjustment - New checkGridSkew() detects imbalanced grid - autoAdjustGrid() reinitializes around current price - Prevents grid from becoming ineffective after drift - Triggers when one side is 3x more filled than other * fix(grid): recalculate bounds in autoAdjustGrid before reinitializing levels Critical fix for grid auto-adjustment: - Recalculate grid bounds (UpperPrice, LowerPrice, GridSpacing) centered on current price before reinitializing grid levels - Preserve filled positions during adjustment by saving and restoring them to the closest new level after reinitialization - Hold mutex lock for the entire adjustment operation to ensure atomicity - Add locked variants of calculateDefaultBounds, calculateATRBounds, and initializeGridLevels to use during adjustment Without this fix, autoAdjustGrid was using old boundaries when creating new grid levels, defeating the purpose of auto-adjustment when price moved significantly. * fix(grid): improve order state sync logic - Don't assume missing orders are filled - Compare position size to determine fill vs cancel - Properly reset cancelled orders to empty state - More accurate grid state tracking * fix(grid): use actual PositionSize sum instead of count in syncGridState heuristic The position-based heuristic was using `float64(previousFilledCount) * level.OrderQuantity` which incorrectly assumed uniform order quantities. Since the grid uses weighted distribution (gaussian, pyramid, uniform) where orders have different quantities, this could lead to incorrect fill detection. Now sums the actual PositionSize from filled levels for accurate comparison. Also adds warning log when GetPositions() fails. * docs: add grid market regime detection design Design for enhanced market state recognition with: - Multi-dimensional indicators (ATR, Bollinger, EMA, MACD, RSI) - Multi-period box indicators (72/240/500 1h candles) - 4-level ranging classification - Breakout detection and handling - Frontend risk control panel * docs: add grid market regime implementation plan 20 tasks covering: - Donchian channel calculation - Box data types and API - Regime classification (4 levels) - Breakout detection and handling - False breakout recovery - Frontend risk panel - AI prompt updates * feat(market): add Donchian channel calculation Add calculateDonchian function to compute highest high and lowest low over a specified period. This is the foundation for box (range) detection in the multi-period box indicator system for grid trading. * fix(market): handle invalid period in calculateDonchian * feat(market): add BoxData and RegimeLevel types * feat(market): add GetBoxData for multi-period box calculation Adds calculateBoxData internal function and GetBoxData public API that fetches 1h klines and computes three Donchian box levels (short/mid/long). This will be used by the grid trading system to detect market regime. * feat(store): add box and regime fields to grid models * feat(trader): add regime classification and breakout detection Implements Tasks 6-9 for grid market regime awareness: - Task 6: classifyRegimeLevel with Bollinger/ATR thresholds - Task 7: detectBoxBreakout for multi-period box breakouts - Task 8: confirmBreakout with 3-candle confirmation logic - Task 9: getBreakoutAction mapping breakout levels to actions * feat(trader): integrate box breakout detection into grid cycle - Task 10: Add checkBoxBreakout with 3-candle confirmation - Task 11: Add checkFalseBreakoutRecovery for 50% position recovery - Task 12: Add box/breakout/regime fields to GridState * feat: add grid risk panel with API endpoint - Task 13: Add GridRiskInfo type to frontend - Task 14: Add /traders/:id/grid-risk API endpoint - Task 15: Add GetGridRiskInfo method to AutoTrader - Task 16: Create GridRiskPanel component with i18n * feat(kernel): add box indicators to AI prompt - Add BoxData field to GridContext - Add box indicator table to both zh/en prompts - Show breakout/warning alerts based on price position * feat(web): integrate GridRiskPanel into TraderDashboardPage * feat(lighter): improve API key validation and market caching - Add API key validation status tracking - Add market list caching to reduce API calls - Improve logging (debug vs info levels) - Add comprehensive integration tests - Update trader manager and store for lighter support * fix: remove hardcoded test wallet address * fix(grid): improve GridRiskPanel layout and fix liquidation data - Make panel collapsible with summary badges when collapsed - Use compact 2-column grid layout for detailed info - Fix auth token key (token -> auth_token) - Only calculate liquidation distance when position exists * fix(grid): add isRunning checks to prevent trades after Stop() is called
This commit is contained in:
tinkle-community
GitHub
@@ -1210,3 +1210,91 @@ func ExportCalculateATR(klines []Kline, period int) float64 {
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func ExportCalculateBOLL(klines []Kline, period int, multiplier float64) (upper, middle, lower float64) {
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return calculateBOLL(klines, period, multiplier)
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}
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// calculateDonchian calculates Donchian channel (highest high, lowest low) for given period
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func calculateDonchian(klines []Kline, period int) (upper, lower float64) {
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if len(klines) == 0 || period <= 0 {
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return 0, 0
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}
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// Use all available klines if period > len(klines)
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start := len(klines) - period
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if start < 0 {
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start = 0
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}
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upper = klines[start].High
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lower = klines[start].Low
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for i := start + 1; i < len(klines); i++ {
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if klines[i].High > upper {
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upper = klines[i].High
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}
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if klines[i].Low < lower {
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lower = klines[i].Low
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}
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}
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return upper, lower
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}
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// ExportCalculateDonchian exports calculateDonchian for testing
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func ExportCalculateDonchian(klines []Kline, period int) (float64, float64) {
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return calculateDonchian(klines, period)
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}
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// Box period constants (in 1h candles)
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const (
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ShortBoxPeriod = 72 // 3 days of 1h candles
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MidBoxPeriod = 240 // 10 days of 1h candles
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LongBoxPeriod = 500 // ~21 days of 1h candles
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)
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// calculateBoxData calculates multi-period box data from klines
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func calculateBoxData(klines []Kline, currentPrice float64) *BoxData {
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box := &BoxData{
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CurrentPrice: currentPrice,
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}
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if len(klines) == 0 {
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return box
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}
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box.ShortUpper, box.ShortLower = calculateDonchian(klines, ShortBoxPeriod)
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box.MidUpper, box.MidLower = calculateDonchian(klines, MidBoxPeriod)
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box.LongUpper, box.LongLower = calculateDonchian(klines, LongBoxPeriod)
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return box
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}
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// ExportCalculateBoxData exports calculateBoxData for testing
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func ExportCalculateBoxData(klines []Kline, currentPrice float64) *BoxData {
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return calculateBoxData(klines, currentPrice)
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}
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// GetBoxData fetches 1h klines and calculates box data for a symbol
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func GetBoxData(symbol string) (*BoxData, error) {
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symbol = Normalize(symbol)
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// Fetch 500 1h klines
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var klines []Kline
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var err error
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if IsXyzDexAsset(symbol) {
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klines, err = getKlinesFromHyperliquid(symbol, "1h", LongBoxPeriod)
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} else {
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klines, err = getKlinesFromCoinAnk(symbol, "1h", LongBoxPeriod)
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}
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if err != nil {
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return nil, fmt.Errorf("failed to get 1h klines: %w", err)
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}
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if len(klines) == 0 {
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return nil, fmt.Errorf("no kline data available")
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}
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currentPrice := klines[len(klines)-1].Close
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return calculateBoxData(klines, currentPrice), nil
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}
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@@ -500,3 +500,86 @@ func TestIsStaleData_EmptyKlines(t *testing.T) {
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t.Error("Expected false for empty klines, got true")
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}
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}
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func TestCalculateDonchian(t *testing.T) {
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// Create test klines with known high/low values
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klines := []Kline{
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{High: 100, Low: 90},
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{High: 105, Low: 88},
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{High: 102, Low: 92},
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{High: 108, Low: 85},
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{High: 103, Low: 91},
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}
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upper, lower := ExportCalculateDonchian(klines, 5)
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if upper != 108 {
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t.Errorf("Expected upper = 108, got %v", upper)
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}
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if lower != 85 {
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t.Errorf("Expected lower = 85, got %v", lower)
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}
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}
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func TestCalculateDonchian_PartialPeriod(t *testing.T) {
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klines := []Kline{
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{High: 100, Low: 90},
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{High: 105, Low: 88},
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}
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upper, lower := ExportCalculateDonchian(klines, 10)
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// Should use all available klines when period > len(klines)
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if upper != 105 {
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t.Errorf("Expected upper = 105, got %v", upper)
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}
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if lower != 88 {
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t.Errorf("Expected lower = 88, got %v", lower)
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}
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}
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func TestCalculateDonchian_InvalidPeriod(t *testing.T) {
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klines := []Kline{
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{High: 100, Low: 90},
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}
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// Zero period should return (0, 0)
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upper, lower := ExportCalculateDonchian(klines, 0)
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if upper != 0 || lower != 0 {
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t.Errorf("Expected (0, 0) for zero period, got (%v, %v)", upper, lower)
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}
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// Negative period should return (0, 0)
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upper, lower = ExportCalculateDonchian(klines, -1)
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if upper != 0 || lower != 0 {
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t.Errorf("Expected (0, 0) for negative period, got (%v, %v)", upper, lower)
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}
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}
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func TestCalculateBoxData(t *testing.T) {
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// Create synthetic kline data
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klines := make([]Kline, 500)
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for i := 0; i < 500; i++ {
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basePrice := 100.0
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klines[i] = Kline{
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High: basePrice + float64(i%10),
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Low: basePrice - float64(i%10),
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Close: basePrice,
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}
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}
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box := ExportCalculateBoxData(klines, 100.0)
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if box.ShortUpper == 0 || box.ShortLower == 0 {
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t.Error("Short box should not be zero")
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}
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if box.MidUpper == 0 || box.MidLower == 0 {
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t.Error("Mid box should not be zero")
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}
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if box.LongUpper == 0 || box.LongLower == 0 {
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t.Error("Long box should not be zero")
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}
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if box.CurrentPrice != 100.0 {
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t.Errorf("Expected CurrentPrice = 100.0, got %v", box.CurrentPrice)
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}
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}
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@@ -187,3 +187,42 @@ var config = Config{
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},
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UpdateInterval: 60, // 1 minute
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}
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// BoxData represents multi-period Donchian channel (box) data
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type BoxData struct {
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// Short-term box (72 1h candles = 3 days)
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ShortUpper float64 `json:"short_upper"`
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ShortLower float64 `json:"short_lower"`
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// Mid-term box (240 1h candles = 10 days)
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MidUpper float64 `json:"mid_upper"`
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MidLower float64 `json:"mid_lower"`
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// Long-term box (500 1h candles = ~21 days)
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LongUpper float64 `json:"long_upper"`
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LongLower float64 `json:"long_lower"`
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// Current price position relative to boxes
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CurrentPrice float64 `json:"current_price"`
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}
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// RegimeLevel represents the ranging classification level
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type RegimeLevel string
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const (
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RegimeLevelNarrow RegimeLevel = "narrow" // 窄幅震荡
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RegimeLevelStandard RegimeLevel = "standard" // 标准震荡
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RegimeLevelWide RegimeLevel = "wide" // 宽幅震荡
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RegimeLevelVolatile RegimeLevel = "volatile" // 剧烈震荡
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RegimeLevelTrending RegimeLevel = "trending" // 趋势
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)
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// BreakoutLevel represents which box level has been broken
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type BreakoutLevel string
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const (
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BreakoutNone BreakoutLevel = "none"
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BreakoutShort BreakoutLevel = "short"
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BreakoutMid BreakoutLevel = "mid"
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BreakoutLong BreakoutLevel = "long"
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)
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